Studying stellar binary systems with the Laser Interferometer Space Antenna using delayed rejection Markov chain Monte Carlo methods

被引：4
|
作者：
Trias, Miquel [1 ]
Vecchio, Alberto [2 ]
Veitch, John [2 ]
机构：
[1] Univ Illes Balears, Dept Fis, E-07122 Palma de Mallorca, Spain
[2] Univ Birmingham, Sch Phys & Astron, Birmingham B15 2TT, W Midlands, England
来源：
CLASSICAL AND QUANTUM GRAVITY | 2009年 / 26卷 / 20期
基金：
英国科学技术设施理事会;
关键词：
INFERENCE;
D O I：
10.1088/0264-9381/26/20/204024
中图分类号：
P1 [天文学];
学科分类号：
0704 ;
摘要：
Bayesian analysis of Laser Interferometer Space Antenna (LISA) data sets based on Markov chain Monte Carlo methods has been shown to be a challenging problem, in part due to the complicated structure of the likelihood function consisting of several isolated local maxima that dramatically reduces the efficiency of the sampling techniques. Here we introduce a new fully Markovian algorithm, a delayed rejection Metropolis-Hastings Markov chain Monte Carlo method, to efficiently explore these kind of structures and we demonstrate its performance on selected LISA data sets containing a known number of stellar-mass binary signals embedded in Gaussian stationary noise.
引用
收藏
页数：11
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